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» Sampling Bounds for Stochastic Optimization
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ICML
2009
IEEE
14 years 10 months ago
Near-Bayesian exploration in polynomial time
We consider the exploration/exploitation problem in reinforcement learning (RL). The Bayesian approach to model-based RL offers an elegant solution to this problem, by considering...
J. Zico Kolter, Andrew Y. Ng
CDC
2008
IEEE
145views Control Systems» more  CDC 2008»
13 years 10 months ago
Necessary and sufficient conditions for success of the nuclear norm heuristic for rank minimization
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in control theory, machine learning, and discrete geometry. This c...
Benjamin Recht, Weiyu Xu, Babak Hassibi
AI
2008
Springer
13 years 10 months ago
Sequential Monte Carlo in reachability heuristics for probabilistic planning
The current best conformant probabilistic planners encode the problem as a bounded length CSP or SAT problem. While these approaches can find optimal solutions for given plan leng...
Daniel Bryce, Subbarao Kambhampati, David E. Smith
SAB
2004
Springer
198views Optimization» more  SAB 2004»
14 years 3 months ago
A Review of Probabilistic Macroscopic Models for Swarm Robotic Systems
Abstract. In this paper, we review methods used for macroscopic modeling and analyzing collective behavior of swarm robotic systems. Although the behavior of an individual robot in...
Kristina Lerman, Alcherio Martinoli, Aram Galstyan
PODS
2009
ACM
119views Database» more  PODS 2009»
14 years 10 months ago
Exceeding expectations and clustering uncertain data
Database technology is playing an increasingly important role in understanding and solving large-scale and complex scientific and societal problems and phenomena, for instance, un...
Sudipto Guha, Kamesh Munagala